Fine granularity scalability (FGS) includes a multitude of audio coding applications such as real-time multimedia streaming and dynamic multimedia storage. In particular, FGS has been adopted by the Motion Picture Experts Group (MPEG) and incorporated into the MPEG 4 international standard, including AAC.
In conventional coding such as AAC in MPEG-4, first codes of the information are used in left and right channels at a place of the header in processing audio signals. The left-channel data are coded and the right-channel data are then coded. That is, coding is processed in the order of the header, left and right channels. When information for the left and right channels are arranged and transmitted irrespective of significance after the header is processed in such a manner, signals for the right channel positioned backwards will disappear first if the bit rate is lowered. The transmission performance will seriously degrade as a result.
In FGS audio coding, a base layer and an enhancement layer are transmitted. The single enhancement layer, after quantization of the data therein, is transmitted with varied bit rates. Truncation of the quantized data also takes place as layer size limits are applied in the enhancement layer. Noise shaping is implemented to minimize quantization noise, under a masking level so it will be imperceptible to the human ear. For noise shaping, psychoacoustics are applied to control errors in the quantization process with scale factors being associated with a plurality of sub-bands. The most important characteristics of human acoustics in coding a digital audio signal include a masking effect (as an audio signal is inaudible due to another signal) and a critical band feature (as noises having the same amplitude are differently perceived when the noise signal is within or without a critical band). These characteristics are utilized so the range of noise allocated within a critical band is calculated in generating quantization noise corresponding to the calculated range to minimize data loss due to the coding. However, errors introduced by the disposal of the truncated data are not governed by the psychoacoustic model.
There is thus a general need in the art for a method and system of audio coding to overcome at least the aforementioned shortcomings in the art. A particular need exists in the art for an optimal method and system in audio coding overcoming performance degradation issues when information in channels are arranged and transmitted irrespective of significance as the bit rate is lowered. A further need exists in the art for an optimal FGS method and system in audio coding overcoming the limitations of the psychoacoustic model in controlling errors in truncation of quantized data.